Robust, fast, fuss-free MCMC parameter estimation from .net, R, or MatLab
Filzbach is a flexible, fast, robust, parameter estimation engine that allows you to parameterize arbitrary, non-linear models, of the kind that are necessary in biological sciences, against multiple, heterogeneous data sets. Filzbach allows for Bayesian parameter estimation, maximum likelihood analysis, priors, latents, hierarchies, error propagation and model selection, often with just a few lines of code.
Scientific results enabled by Filzbach have been published in tens of peer-reviewed publications. For more details see the list of publications below, and the Computational Science Lab tools page.
You can also build Filzbach library from sources (GitHub) using GNU g++ or Microsoft Visual C++.
Traditionally, ecology and biology has been largely split into the purely empirical (generating or analysing data with only informal use of models) and the purely theoretical (analysing ideas-rich models that have been, at best, only informally constrained with data). However, to create a precise, predictive, understanding of ecological and biological systems it is necessary to bridge this gap, using data to formally parameterize, and select between, aribtrary, ideas-rich models.
- Specify parameters, define the likelihood, and Filzbach does the rest
- The automatic adaptive MCMC sampling algorithm copes with a wide range of different problems with no need for any manual tuning
- Automatic handling of multiple chains, testing for convergence, calculation of MLEs, posterior means and credible intervals on all parameters; and AIC, BIC, DIC
- Easy error propagation of parameter uncertainty through any model
- Fast and robust compared to commonly used alternatives
- Comes with a library of easy to use parameter distributions -- but can be extended include any others, so long as they are written in C
- FilzbachR makes the power of Filzbach available through R, and crucially, allows the user to specify the model, and the likelihood, in R itself. This allows for Filzbach analyses that use any of the stats and libraries already available in R
- Similarly, FilzbachMatlab will make the power of Filzbach available in MatLab. FilzbachMatLab is not yet released, but watch this space, and feel free to contact us for more details
To try online, download, and learn more, see the Filzbach section of our new tool site.
- Gian Marco Palamara, Dylan Z. Childs, Christopher F. Clements, Owen L. Petchey, Marco Plebani, and Matthew J. Smith, Inferring the temperature dependence of population parameters: the effects of experimental design and inference algorithm , in Ecology and Evolution, 1 October 2014.
- Isabel M D Rosa, Drew Purves, Carlos Souza Jr, and Robert M Ewers, Predictive Modelling of Contagious Deforestation in the Brazilian Amazon, in PLOS One, PLoS, October 2013.
- Mark C Vanderwel, Vassily S Lyutsarev, and Drew W Purves, Climate-related variation in mortality and recruitment determine regional forest-type distributions, in Global Ecology and Biogeography, Wiley, 4 June 2013.
- Mark C Vanderwel and Drew W Purves, How do disturbances and environmental heterogeneity affect the pace of forest distribution shifts under climate change?, in Ecography, Wiley, June 2013.
- M. J. Smith, D. W. Purves, M. C. Vanderwel, V. Lyutsarev, and S. Emmott, The climate dependence of the terrestrial carbon cycle, including parameter and structural uncertainties, in Biogeosciences, vol. 10, pp. 583-606, European Geosciences Union, 29 January 2013.
- L.N. Joppa and R Williams, Modeling the Building Blocks of Biodiversity, in PLoS ONE, vol. 8, no. 2, pp. e56277, 2013.
- Raul Garcia-Valdes, Miguel A Zavala, Migueal B Araujo, and Drew W Purves, Chasing a moving target: projecting climate change-induced shifts in non-equilibrial tree species distributions, in Journal of Ecology, British Ecological Society, January 2013.
- Mark C Vanderwel, David A Coomes, and Drew W Purves, Quantifying variation in forest disturbance, and its effects on aboveground biomass dynamics, across the eastern United States, in Global Change Biology, Wiley, January 2013.
- Tim Newbold, Jorn P W Scharlemann, Stuart H M Butchart, Cagan A Sekercioglu, Rob Alkemade, Hollie Booth, and Drew W Purves, Ecological traits affect the response of tropical forest bird species to land-use intensity, in Proceedings of the Royal Society of London, Series B, The Royal Society, November 2012.
- Matthew J. Smith, Mark C. Vanderwel, Vassily Lyutsarev, Stephen Emmott, and Drew W. Purves, The climate dependence of the terrestrial carbon cycle; including parameter and structural uncertainties, in Biogeosciences Discussions, vol. 9, pp. 13439-13496, European Geosciences Union, 4 October 2012.
- Emily R Lines, Miguel A Zavala, Drew W Purves, and David A Coomes, Predictable changes in aboveground allometry of trees along gradients of temperature, aridity and competition, in Global Ecology and Biogeography, Wiley, February 2012.
- Drew Purves and Mark Vanderwel, (book chapter in press) Traits States and Rates: Understanding Coexistence in Forests , in Forests and Global Change, Cambridge University Press, 2012.
- John P. Caspersen, Mark C. Vanderwel, William G. Cole, and Drew W. Purves, How stand productivity results from size- and competition-dependent growth and mortality, in PLoS ONE, vol. 6, no. 12, pp. e28660, December 2011.
- Neil Dalchau, Andrew Phillips, Leonard D Goldstein, Mark Howarth, Luca Cardelli, Stephen Emmott, Tim Elliott, and Joern M Werner, A peptide filtering relation quantifies MHC class I peptide optimization, in PLoS Computational Biology, vol. 7, no. 10, pp. e1002144, PLoS, 13 October 2011.
- Richard J. Williams and Drew W. Purves, The probabilistic niche model reveals substantial variation in the niche structure of empirical food webs, in Ecology, 19 September 2011.
- C.E. Timothy Paine, Toby R Marthews, Deborah R Vogt, Drew Purves, Mark Rees, Andy Hector, and Lindsay A Turnbull, How to fit nonlinear plant growth models and calculate growth rates: an update for ecologists, in Methods in Ecology and Evolution, British Ecological Society, September 2011.
- Greg McInerny and Drew Purves, Fine-scale environmental variation in species distribution modelling: regression dilution, latent variables and neighbourly advice, in Methods in Ecology and Evolution, British Ecological Society, 25 January 2011.
- L.N. Joppa, D.L. Roberts, N. Myers, and S.L. Pimm, Biodiversity hotspots house the majority of missing species., in Proceedings of the National Academy of Sciences, 2011.
- Alexander A Barron, Drew W Purves, and Lars O Hedin, Facultative nitrogen fixation by canopy legumes in a lowland tropical forest , in Oecologia, Springer Verlag, November 2010.
- Emily R Lines, David A Coomes, and Drew Purves, Influences of Forest Structure, Climate and Species Composition on Tree Mortality across the Eastern US, in PLoS-One, vol. 5, no. 10, PLoS, October 2010.
- Rich Williams, Ananthi Anandanadesan, and Drew Purves, The Probabilistic Niche Model Reveals the Niche Structure and Role of Body Size in a Complex Food Web, in PLoS-One, vol. 5, no. e12092, PLoS, August 2010.
- Drew W Purves, Jeremy W Lichstein, Nikolay Strigul, and Stephen W Pacala, Predicting and understanding forest dynamics using a simple tractable model, in Proceedings of the National Academy of Sciences USA, 29 October 2008.
- Lindsay A Turnbull, Cloe Paul-Victor, Bernhard Schmid, and Drew W Purves, Growth rates, seed size and physiology - Do small-seeded species really grow faster?, in Ecology, vol. 89, pp. 1352-1363, January 2008.
- Drew W Purves, Jeremy W Lichstein, and Stephen W Pacala, Crown Plasticity and Competition for Canopy Space: A New Spatially Implicit Model Parameterized for 250 North American Tree Species, in PLoS-One, vol. 2, no. 9, pp. e870, January 2007.